首页> 外文期刊>Marine pollution bulletin >Identification of fuel samples from the Prestige wreckage by pattern recognition methods
【24h】

Identification of fuel samples from the Prestige wreckage by pattern recognition methods

机译:通过模式识别方法识别声望残骸中的燃料样品

获取原文
获取原文并翻译 | 示例
       

摘要

A set of 34 worldwide crude oils, 12 distilled products (kerosene, gas oils, and fuel oils) and 45 oil samples taken from several Galician beaches (NW Spain) after the wreckage of the Prestige tanker off the Galician coast was studied. Gas chromatography with flame ion-ization detection was combined with chemometric multivariate pattern recognition methods (principal components analysis, cluster analysis and Kohonen neural networks) to differentiate and characterize the Prestige fuel oil. All multivariate studies differentiated between several groups of crude oils, fuel oils, distilled products, and samples belonging to the Prestige's wreck and samples from other illegal discharges. In addition, a reduced set of 13 n-alkanes out of 36, were statistically selected by Procrustes Rotation to cope with the main patterns in the datasets. These variables retained the most important characteristics of the data set and lead to a fast and cheap analytical screening methodology.
机译:在Prestige油轮在加利西亚海岸附近发生残骸后,研究了一组34种全球原油,12种蒸馏产品(煤油,瓦斯油和燃料油)和45个从几个加利西亚海滩(西班牙西北部)采集的油样。带有火焰离子化检测的气相色谱仪与化学计量学的多模式识别方法(主要成分分析,聚类分析和Kohonen神经网络)相结合,以区分和表征Prestige燃料油。所有多变量研究都将原油,燃料油,蒸馏产品和属于Prestige残骸的样品与来自其他非法排放的样品分为几类。此外,通过Procrustes Rotation统计选择了36种还原的13种正构烷烃,以应对数据集中的主要模式。这些变量保留了数据集的最重要特征,并导致了一种快速而廉价的分析筛选方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号